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Vision-Based Smoke Detection Algorithm for Early Fire Recognition in Digital Video Recording System

机译:基于视觉的烟雾探测算法用于数字视频记录系统中的早期火灾识别

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The digital video recording (DVR) closed circuit television (CCTV) system is quickly becoming one of the most accepted security, surveillance documentation, and monitoring in service today. Particularly a lot of catastrophes such as tsunami, volcano, and terrorism cause huge casualty and property loss. In this paper, we concentrate on the smoke detection system in video for early fire alarming. The proposed block-based smoke detection algorithm consists of three basic steps, which has simple operation and provides good performance. In the first step, we discover motion vector utilizing several motion estimation schemes and discern the suspect as smoke region. This process does not require huge computational cost because of using the H.264/AVC during the recoding in DVR system. In the second step, we conduct block based chromatic detection. In the third step, we employ motion information for detecting the correct smoke block by using the characteristics that smoke goes almost upward. Experimental results provide that the proposed method gives good performance for real smoke detection.
机译:数字视频记录(DVR)闭路电视(CCTV)系统正在迅速成为当今服务中最被接受的安全性,监视文档和监视之一。特别是许多灾难,例如海啸,火山和恐怖主义,造成了巨大的人员伤亡和财产损失。在本文中,我们将重点放在视频中的烟雾探测系统上,以进行早期火灾报警。所提出的基于块的烟雾检测算法包括三个基本步骤,它们具有简单的操作并提供良好的性能。第一步,我们使用几种运动估计方案发现运动矢量,并将可疑对象识别为烟雾区域。由于在DVR系统中进行编码时使用H.264 / AVC,因此此过程不需要大量的计算成本。在第二步中,我们进行基于块的色度检测。在第三步中,我们利用运动信息来利用烟雾几乎上升的特征来检测正确的烟雾块。实验结果表明,该方法具有良好的真实烟雾探测性能。

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